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Question 1,304 of 1,740

Monitoring and Logging →hardMultiple ChoiceObjective-mapped

Quick Answer

The answer is to add a second target tracking scaling policy based on average memory utilization with a target value of 75%. This is correct because the root cause is memory pressure, not CPU—the existing CPU-based policy never triggered since utilization stayed below 75%, while memory spiked above 90%, causing garbage collection pauses and timeouts. On the AWS Certified DevOps Engineer Professional DOP-C02 exam, this scenario tests your understanding that ECS memory-based auto scaling with a target tracking policy can independently scale tasks based on a different resource metric, and that a single policy may miss critical bottlenecks. A common trap is assuming CPU is always the primary scaling signal, or reaching for static fixes like increasing task memory, which wastes cost and fails to handle dynamic spikes. Remember the memory tip: “CPU sleeps, memory creeps—track both to keep the service deep.”

DOP-C02 Monitoring and Logging Practice Question

This DOP-C02 practice question tests your understanding of monitoring and logging. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

A company runs a containerized web application on Amazon ECS with AWS Fargate. The application is critical and requires high availability. The DevOps team has set up an Amazon CloudWatch alarm that triggers an auto scaling action when the average CPU utilization exceeds 75% for 5 minutes. However, during a recent traffic spike, the application became slow and some requests timed out, even though the CloudWatch alarm did not fire. The team checked the ECS service auto scaling configuration and found that the target tracking scaling policy based on average CPU utilization is set with a target value of 75%. The ECS service is configured with a minimum of 2 tasks and a maximum of 10 tasks. Upon investigation, they noticed that the CPU utilization metric for the service remained below 75% during the spike, but the memory utilization was high (over 90%). The application logs show that the tasks were running out of memory, causing garbage collection pauses and slow responses. Which course of action should the DevOps engineer take to prevent this issue in the future?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

Question 1hardmultiple choice

Full question →

A
Add a second target tracking scaling policy based on average memory utilization with a target value of 75%.
Memory-based scaling will add tasks when memory is high, preventing memory exhaustion.
B
Decrease the CPU target value to 50% to trigger scaling earlier.
Why wrong: The issue is memory, not CPU; scaling on CPU would not help.
C
Increase the minimum number of tasks from 2 to 5 to provide more capacity upfront.
Why wrong: Increasing minimum tasks adds static capacity but does not dynamically respond to memory spikes, and may increase cost.
D
Increase the task memory limit in the task definition to 8 GB.
Why wrong: Increasing memory limit statically may not handle dynamic spikes and could be cost-inefficient; auto scaling based on memory is a better approach.

Full breakdown with real-world context →

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Add a second target tracking scaling policy based on average memory utilization with a target value of 75%.

Option B is correct because the issue is memory pressure, not CPU. Adding a target tracking scaling policy based on memory utilization will scale the service when memory is high. Option A is wrong because increasing the minimum number of tasks would not dynamically respond to memory spikes. Option C is wrong because the issue is not CPU. Option D is wrong because the application is already containerized; increasing task memory is a static change that may not handle dynamic spikes efficiently, and the best practice is to auto scale based on memory.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✓
Add a second target tracking scaling policy based on average memory utilization with a target value of 75%.
Why this is correct
Memory-based scaling will add tasks when memory is high, preventing memory exhaustion.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Decrease the CPU target value to 50% to trigger scaling earlier.
Why it's wrong here
The issue is memory, not CPU; scaling on CPU would not help.
✗
Increase the minimum number of tasks from 2 to 5 to provide more capacity upfront.
Why it's wrong here
Increasing minimum tasks adds static capacity but does not dynamically respond to memory spikes, and may increase cost.
✗
Increase the task memory limit in the task definition to 8 GB.
Why it's wrong here
Increasing memory limit statically may not handle dynamic spikes and could be cost-inefficient; auto scaling based on memory is a better approach.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.

Detailed technical explanation

How to think about this question

This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.

KKey Concepts to Remember

Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.

TExam Day Tips

Underline the problem statement mentally.
Watch for words such as best, first, most likely and least administrative effort.
Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.

What to study next

Got this wrong? Here's your next step.

Identify which DOP-C02 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.

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FAQ

Questions learners often ask

What does this DOP-C02 question test?

Monitoring and Logging — This question tests Monitoring and Logging — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Add a second target tracking scaling policy based on average memory utilization with a target value of 75%. — Option B is correct because the issue is memory pressure, not CPU. Adding a target tracking scaling policy based on memory utilization will scale the service when memory is high. Option A is wrong because increasing the minimum number of tasks would not dynamically respond to memory spikes. Option C is wrong because the issue is not CPU. Option D is wrong because the application is already containerized; increasing task memory is a static change that may not handle dynamic spikes efficiently, and the best practice is to auto scale based on memory.

What should I do if I get this DOP-C02 question wrong?

Are there clue words in this question I should notice?

Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

About these practice questions

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Same concept, more angles

1 more ways this is tested on DOP-C02

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. A company has deployed a containerized application on Amazon ECS with Fargate. The application is fronted by an Application Load Balancer (ALB). The DevOps team is using CloudWatch Container Insights to monitor the ECS cluster. They notice that the 'MemoryUtilized' metric for the service is consistently above 80%, and the 'CPUUtilized' is around 50%. The ALB's 'TargetResponseTime' is increasing over time. The team wants to resolve the performance issue. Which action should the team take?

medium

✓ A.Increase the memory limit for the ECS task definition to allow the container to use more memory.
B.Increase the CPU limit for the ECS task definition to improve performance.
C.Increase the number of ALB targets by adding more availability zones.
D.Increase the desired count of the ECS service to distribute the load across more tasks.

Why A: Option B is correct because the high memory utilization (above 80%) is likely causing performance degradation. Increasing the memory limit for the task definition will allow the container to handle more load. Option A is wrong because CPU is not the bottleneck. Option C is wrong because scaling the ALB does not address the container's resource limits. Option D is wrong because increasing the desired count without fixing the memory limit may not help if each task is memory-constrained.

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Question Discussion

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This DOP-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DOP-C02 exam.